Designing of Insecticides Against Bemisia tabaci targeting
ecdysone receptor

a 2023

Designing of Insecticides Against Bemisia tabaci targeting ecdysone receptor

., Indu, Jozef HRITZ, Václav BRÁZDA, Rajesh KUMAR, Krishnendu BERA et. al.

Základní údaje

Originální název

Designing of Insecticides Against Bemisia tabaci targeting ecdysone receptor

Autoři

., Indu, Jozef HRITZ, Václav BRÁZDA, Rajesh KUMAR a Krishnendu BERA

Vydání

6th Advanced in Silico Drug Design workshop/challenge, 30st January – 3rd February 2023, Faculty of Science, Palacky University, Olomouc, Czech Republic, 2023

Další údaje

Typ výsledku

Konferenční abstrakt

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Abstract Book

Změněno: 4. 2. 2023 11:04, Krishnendu Bera, Ph.D.

Anotace

V originále

Bemisia tabaci is a major destructive pest that destroys more than 600 crop species worldwide. It is also responsible for transferring more than 100 viruses in plants which interferes with plant growth by becoming a limiting growth factor. This project aims to find novel lead molecules using computational approaches. The ecdysone receptor of B tabaci is involved in metamorphosis, cell differentiation and reproduction processes. No similar protein is present in mammals which makes it an ideal target. The unavailability of a full-length structure in PDB lead us to model the full-length protein using Alphafold 2.2.0 1. The disordered regions of the protein were predicted by using IDP predictor software, i.e. DEPICTER 2. Further, 32,552 bacterial and fungal secondary metabolites were retrieved from the npatlas 2.0 database 3 and docked each metabolite with the simulation obtained last conformation of EcR protein using idock 2.2.3 software 4. I have chosen a cut-off -10 kcal/mol binding energy and found 14 metabolites. I have redock these 14 metabolites again with Autodock vina 1.1.2 5 to validate idock 2.2.3 results and found an almost similar result with minor deviations. These dockings were compared with 20E, a natural hormone binding with EcR protein. Lastly, one compound K6323 with the most suitable scoring function were selected for 30 ns MD simulations of the protein complex with E20 and K6323 and compared with apo form of the protein. Further, QMMM/GBSA-based binding energy was calculated from 100 snapshots from MD simulation. The binding energy of K6323 was found to be better than the natural inhibitor 20E. These computational predictions can be analysed further experimentally.

References:

1. Berendsen, H. J. C., van der Spoel, D., & van Drunen, R. (1995) Computer Physics Communications.

2. Carmichael, J. A., et al. (2005). J. of Biological Chem., 280(23), 22258–22269.

3. Barro D. et al. (2011). Annual Review of Entomology, 56(1), 1–19.

Návaznosti

GF20-05789L, projekt VaV

Název: Charakterizace přirozeně neuspořádaných proteinů

Investor: Grantová agentura ČR, Characterization of intrinsically disordered proteins, Partnerská agentura (Rakousko)

LM2018140, projekt VaV

Název: e-Infrastruktura CZ (Akronym: e-INFRA CZ)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, e-Infrastruktura CZ

MUNI/G/1002/2021, interní kód MU

Název: Insight into CAIX structure and function and design of selective inhibitors as potential anti-cancer drugs (Akronym: CAIX-target)

Investor: Masarykova univerzita, Insight into CAIX structure and function and design of selective inhibitors as potential anti-cancer drugs, INTERDISCIPLINARY - Mezioborové výzkumné projekty

Citovat

., Indu, Jozef HRITZ, Václav BRÁZDA, Rajesh KUMAR a Krishnendu BERA. Designing of Insecticides Against Bemisia tabaci targeting ecdysone receptor. In BERA, Krishnendu. 6th Advanced in Silico Drug Design workshop/challenge, 30st January – 3rd February 2023, Faculty of Science, Palacky University, Olomouc, Czech Republic. 2023.

@proceedings{2252558,
   author = {., Indu and Hritz, Jozef and Brázda, Václav and Kumar, Rajesh and Bera, Krishnendu},
   booktitle = {6th Advanced in Silico Drug Design workshop/challenge, 30st January – 3rd February 2023, Faculty of Science, Palacky University, Olomouc, Czech Republic},
   title = {Designing of Insecticides Against Bemisia tabaci targeting ecdysone receptor},
   url = {https://www.kfc.upol.cz/wp-content/uploads/2023/01/6ADD_BoA.pdf},
   year = {2023}
}

TY  - CONF
ID  - 2252558
AU  - ., Indu - Hritz, Jozef - Brázda, Václav - Kumar, Rajesh - Bera, Krishnendu
PY  - 2023
TI  - Designing of Insecticides Against Bemisia tabaci targeting ecdysone receptor
UR  - https://www.kfc.upol.cz/wp-content/uploads/2023/01/6ADD_BoA.pdf
N2  - Bemisia tabaci is a major destructive pest that destroys more than 600 crop species worldwide. It is also responsible for transferring more than 100 viruses in plants which interferes with plant growth by becoming a limiting growth factor. This project aims to find novel lead molecules using computational approaches. The ecdysone receptor of B tabaci is involved in metamorphosis, cell differentiation and reproduction processes. No similar protein is present in mammals which makes it an ideal target. The unavailability of a full-length structure in PDB lead us to model the full-length protein using Alphafold 2.2.0 1. The disordered regions of the protein were predicted by using IDP predictor software, i.e. DEPICTER 2. Further, 32,552 bacterial and fungal secondary metabolites were retrieved from the npatlas 2.0 database 3 and docked each metabolite with the simulation obtained last conformation of EcR protein using idock 2.2.3 software 4. I have chosen a cut-off -10 kcal/mol binding energy and found 14 metabolites. I have redock these 14 metabolites again with Autodock vina 1.1.2 5 to validate idock 2.2.3 results and found an almost similar result with minor deviations. These dockings were compared with 20E, a natural hormone binding with EcR protein. Lastly, one compound K6323 with the most suitable scoring function were selected for 30 ns MD simulations of the protein complex with E20 and K6323 and compared with apo form of the protein. Further, QMMM/GBSA-based binding energy was calculated from 100 snapshots from MD simulation. The binding energy of K6323 was found to be better than the natural inhibitor 20E. These computational predictions can be analysed further experimentally.

References:

1. Berendsen, H. J. C., van der Spoel, D., & van Drunen, R. (1995) Computer Physics Communications.

2. Carmichael, J. A., et al. (2005). J. of Biological Chem., 280(23), 22258–22269.

3. Barro D. et al. (2011). Annual Review of Entomology, 56(1), 1–19.

ER -

., Indu, Jozef HRITZ, Václav BRÁZDA, Rajesh KUMAR a Krishnendu BERA. Designing of Insecticides Against Bemisia tabaci targeting ecdysone receptor. In BERA, Krishnendu. \textit{6th Advanced in Silico Drug Design workshop/challenge, 30st January – 3rd February 2023, Faculty of Science, Palacky University, Olomouc, Czech Republic}. 2023.

Podrobný výpis o publikaci